游戏编程模式20-优化模式-空间分区

优化模式-空间分区

参考章节：https://gpp.tkchu.me/spatial-partition.html

脑内画面

空间分区把世界切成格子、树或区域，让"找附近对象"不再扫描全世界。它像城市邮编：要找附近的人，先看同一片区，而不是挨家挨户问完整座城市。
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Cell 0,0
Cell 1,0
Cell 0,1
Unit A
Unit B
Unit C

它解决的问题

碰撞检测、范围技能、AI 感知、拾取物查询都需要找附近对象。如果每个对象都和所有对象比较，复杂度会接近 O(n^2)。空间分区先缩小候选集，再做精确判断。

C# 示例

csharp 复制代码

public sealed class SpatialGrid<T> where T : notnull
{
    private readonly float _cellSize;
    private readonly Dictionary<(int X, int Y), HashSet<T>> _cells = new();
    private readonly Dictionary<T, (int X, int Y)> _positions = new();

    public SpatialGrid(float cellSize)
    {
        _cellSize = cellSize;
    }

    public void Insert(T item, float x, float y)
    {
        var cell = ToCell(x, y);

        if (!_cells.TryGetValue(cell, out var items))
        {
            items = new HashSet<T>();
            _cells[cell] = items;
        }

        items.Add(item);
        _positions[item] = cell;
    }

    public void Move(T item, float x, float y)
    {
        var next = ToCell(x, y);

        if (_positions.TryGetValue(item, out var current) && current == next)
        {
            return;
        }

        Remove(item);
        Insert(item, x, y);
    }

    public void Remove(T item)
    {
        if (!_positions.Remove(item, out var cell))
        {
            return;
        }

        if (_cells.TryGetValue(cell, out var items))
        {
            items.Remove(item);
        }
    }

    public IEnumerable<T> QueryNearby(float x, float y)
    {
        var center = ToCell(x, y);

        for (var dx = -1; dx <= 1; dx++)
        for (var dy = -1; dy <= 1; dy++)
        {
            var cell = (center.X + dx, center.Y + dy);

            if (!_cells.TryGetValue(cell, out var items))
            {
                continue;
            }

            foreach (var item in items)
            {
                yield return item;
            }
        }
    }

    private (int X, int Y) ToCell(float x, float y)
    {
        return ((int)MathF.Floor(x / _cellSize), (int)MathF.Floor(y / _cellSize));
    }
}

什么时候用

大量对象需要按距离、区域、碰撞范围查询。
全量扫描已经成为性能瓶颈。
世界可以被合理划分成格子、树、区块或关卡房间。

使用时的锋利边

分区结构只负责减少候选集，不负责替代精确检测。格子里找到的对象仍然要做距离、碰撞体、阵营等最终判断。

分区粒度很关键。格子太大，候选集仍然很多；格子太小，对象跨格移动和查询邻居的成本会上升。